<h1 id="texas-congressional-districts">2010 Texas Congressional
Districts</h1>
<h2 id="redistricting-requirements">Redistricting requirements</h2>
<p>In Texas, districts must meet US constitutional requirements, but
there are <a
href="https://redistricting.capitol.texas.gov/pdf/Guide_to_2011_Redistricting.pdf">no
state-specific statutes</a>.</p>
<h3 id="algorithmic-constraints">Algorithmic Constraints</h3>
<p>We enforce a maximum population deviation of 0.5%.</p>
<h2 id="data-sources">Data Sources</h2>
<p>Data for Texas comes from the ALARM Project’s <a
href="https://alarm-redist.github.io/posts/2021-08-10-census-2020/">2020
Redistricting Data Files</a>. We estimate CVAP populations with the
<code>cvap</code> R package.</p>
<h2 id="pre-processing-notes">Pre-processing Notes</h2>
<p>We pre-process the map to split it into clusters for simulation,
which has a slight effect on the types of district plans that will be
sampled.</p>
<h2 id="simulation-notes">Simulation Notes</h2>
<p>We sample 50,000 districting plans for Texas across two independent
runs of the SMC algorithm, and then thin the sample to down to 5,000
plans. We use a pseudo-county constraint to limit the county and
municipality splits. Due to the size and complexity of Texas, we split
the simulations into multiple steps.</p>
<h3 id="clustering-procedure">1. Clustering procedure</h3>
<p>First, we run simulations in three major metropolitan areas: Greater
Houston, a combination of Greater San Antonio and Austin, and
Dallas-Fort Worth. We use collections of counties that define the
Metropolitan Statistical Areas. The counties in each cluster are those
in each Census MSA:</p>
<ul>
<li><p>Houston–The Woodlands–Sugar Land: Austin, Brazoria, Chambers,
Fort Bend, Galveston, Harris, Liberty, Montgomery, Waller.</p></li>
<li><p>Austin–Round Rock-Georgetown: Bastrop, Caldwell, Hays, Travis,
Williamson.</p></li>
<li><p>San Antonio–New Braunfels: Atascosa, Bandera, Bexar, Comal,
Guadalupe, Kendall, Medina, Wilson.</p></li>
<li><p>Dallas–Fort Worth–Arlington: Collin, Dallas, Denton, Ellis, Hunt,
Kaufman, Rockwall, Johnson, Parker, Tarrant, Wise.</p></li>
</ul>
<p>These simulations run the SMC algorithm within each cluster with a
0.25% population tolerance. Because each cluster will have leftover
population, we apply an additional constraint that incentivizes leaving
any unassigned areas on the edge of these clusters to avoid
discontiguities.</p>
<p>In each cluster, we apply hinge Gibbs constraints of strength 3 to
encourage the formation of Hispanic CVAP opportunity districts. In
Houston and Dallas, we also apply a hinge Gibbs constraint of strength 3
to encourage the formation of Black CVAP opportunity districts. These
districts nudge the formation of opportunity districts are above 35%,
and penalize districts with minority populations above 70%.</p>
<h3 id="combination-procedure">2. Combination procedure</h3>
<p>Then, these partial map simulations are combined to run statewide
simulations. We again apply Gibbs hinge constraints to encourage the
formation of minority opportunity districts, with strength 3 to further
encourage Hispanic CVAP opportunity districts.</p>
<h2 id="contents">Contents</h2>
<ul>
<li><code>TX_cd_2010_stats.csv</code> contains summary statistics on the
sampled redistricting plans</li>
<li><code>TX_cd_2010_plans.rds</code> is a compressed
<code>redist_plans</code> object, which contains the matrix of
precinct/block assignments and may be used for further analysis.</li>
<li><code>TX_cd_2010_map.rds</code> is a compressed
<code>redist_map</code> object, which contains the precinct/block
shapefile and demographic data.</li>
</ul>
<p>Both the <code>redist_plans</code> and <code>redist_map</code> object
are intended to be used with the <a
href="https://alarm-redist.github.io/redist/">redist package</a>.</p>
<h3 id="codebook-for-summary-statistics">Codebook for summary
statistics</h3>
<ul>
<li><code>draw</code>: unique identifier for each sample. Non-numeric
draw names are real-world plans, e.g., <code>cd_2010</code> for an
enacted 2010 plan.</li>
<li><code>district</code>: a district identifier. District numbers
roughly match those in the enacted plan, but the correspondence is not
perfect.</li>
<li><code>chain</code>: a number identifying the run of the
redistricting algorithm used to produce this draw. Used for diagnostic
purposes.</li>
<li><code>pop_overlap</code>: a number indicating the fraction of people
in this plan who reside in the same-numbered district in the enacted
plan.</li>
<li><code>total_pop</code>: the total population of each district.</li>
<li><code>total_vap</code>: the total voting-aged population of each
district.</li>
<li><code>pop_*</code>, <code>vap_*</code>: total (voting-aged)
population within racial and ethnic groups for each district. Variable
codes documented <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>plan_dev</code>: the maximum population deviation among
districts in the plan. Computed as
<code>max(abs(distr_pop - target_pop)/target_pop)</code>.</li>
<li><code>comp_edge</code>: compactness, as measured by the fraction of
internal edges kept. Higher values indicate more compactness.</li>
<li><code>comp_polsby</code>: compactness, as measured by the
Polsby-Popper score. Higher values indicate more compactness.</li>
<li><code>county_splits</code>: the number of counties which belong to
more than one district.</li>
<li><code>muni_splits</code>: the number of Census Designated Places
which belong to more than one district.</li>
<li><code>*_##_dem_*</code>, <code>*_##_rep_*</code>: vote counts for
statewide Democratic and Republican candidates in a certain election.
More information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>adv_##</code>, <code>arv_##</code>: average vote counts for
statewide Democratic and Republican candidates in a certain year. More
information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>ndv</code>, <code>nrv</code>: averages of the
<code>adv_##</code> and <code>arv_##</code> variables across all
available elections.</li>
<li><code>ndshare</code>: normal Democratic share, computed as
<code>ndv / (ndv + nrv)</code></li>
<li><code>e_dvs</code>: average Democratic vote share, computed as the
average of the Democratic vote share when first scored under each
statewide election.</li>
<li><code>pr_dem</code>: probability seat is represented by a Democrat;
calculated as the fraction of statewide elections under which the
district had a majority Democratic share.</li>
<li><code>e_dem</code>: expected number of Democratic seats for the
plan; equivalent to summing the <code>pr_dem</code> values across
districts</li>
<li><code>pbias</code>: partisan bias at 50% vote share, averaged across
all available elections. Positive values indicate Republican bias.</li>
<li><code>egap</code>: the efficiency gap, averaged across all available
elections. Positive values indicate Republican bias.</li>
</ul>
